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Extraction and Visualization of TBox Information from SPARQL Endpoints

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Knowledge Engineering and Knowledge Management (EKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10024))

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Abstract

The growing amount of data being published as Linked Data has a huge potential, but the usage of this data is still cumbersome, especially for non-technical users. Visualizations can help to get a better idea of the type and structure of the data available in some SPARQL endpoint, and can provide a useful starting point for querying and analysis. We present an approach for the extraction and visualization of TBox information from Linked Data. SPARQL queries are used to infer concept information from the ABox of a given endpoint, which is then gradually added to an interactive VOWL graph visualization. We implemented the approach in a web application, which was tested on several SPARQL endpoints and evaluated in a qualitative user study with promising results.

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Notes

  1. 1.

    A live demo of LD-VOWL is available at: http://ldvowl.visualdataweb.org.

  2. 2.

    The complete list of questions is available at http://ldvowl.visualdataweb.org.

  3. 3.

    http://data.nobelprize.org/sparql.

  4. 4.

    http://vocabulary.semantic-web.at/PoolParty/sparql/AustrianSkiTeam.

  5. 5.

    http://data.nobelprize.org/terms.

  6. 6.

    http://dbpedia.org/ontology.

  7. 7.

    http://dbpedia.org/class.

  8. 8.

    SPARQL Endpoints Status: http://sparqles.okfn.org.

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Correspondence to Steffen Lohmann .

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Weise, M., Lohmann, S., Haag, F. (2016). Extraction and Visualization of TBox Information from SPARQL Endpoints. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_46

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  • DOI: https://doi.org/10.1007/978-3-319-49004-5_46

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